Mutation Analysis (MutSig 2CV v3.1)
Acute Myeloid Leukemia (Primary blood derived cancer - Peripheral blood)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1QC02C4
Maintained by David Heiman (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Mutation Analysis (MutSig 2CV v3.1). Broad Institute of MIT and Harvard. doi:10.7908/C1QC02C4
Overview
Introduction

This report serves to describe the mutational landscape and properties of a given individual set, as well as rank genes and genesets according to mutational significance. MutSig 2CV v3.1 was used to generate the results found in this report.

  • Working with individual set: LAML-TB

  • Number of patients in set: 195

Input

The input for this pipeline is a set of individuals with the following files associated for each:

  1. An annotated .maf file describing the mutations called for the respective individual, and their properties.

  2. A .wig file that contains information about the coverage of the sample.

Summary

  • MAF used for this analysis:LAML-TB.final_analysis_set.maf

  • Blacklist used for this analysis: pancan_mutation_blacklist.v14.hg19.txt

  • Significantly mutated genes (q ≤ 0.1): 25

Results
Lego Plots

The mutation spectrum is depicted in the lego plots below in which the 96 possible mutation types are subdivided into six large blocks, color-coded to reflect the base substitution type. Each large block is further subdivided into the 16 possible pairs of 5' and 3' neighbors, as listed in the 4x4 trinucleotide context legend. The height of each block corresponds to the mutation frequency for that kind of mutation (counts of mutations normalized by the base coverage in a given bin). The shape of the spectrum is a signature for dominant mutational mechanisms in different tumor types.

Figure 1.  Get High-res Image SNV Mutation rate lego plot for entire set. Each bin is normalized by base coverage for that bin. Colors represent the six SNV types on the upper right. The three-base context for each mutation is labeled in the 4x4 legend on the lower right. The fractional breakdown of SNV counts is shown in the pie chart on the upper left. If this figure is blank, not enough information was provided in the MAF to generate it.

Figure 2.  Get High-res Image SNV Mutation rate lego plots for 4 slices of mutation allele fraction (0<=AF<0.1, 0.1<=AF<0.25, 0.25<=AF<0.5, & 0.5<=AF) . The color code and three-base context legends are the same as the previous figure. If this figure is blank, not enough information was provided in the MAF to generate it.

CoMut Plot

Figure 3.  Get High-res Image The matrix in the center of the figure represents individual mutations in patient samples, color-coded by type of mutation, for the significantly mutated genes. The rate of synonymous and non-synonymous mutations is displayed at the top of the matrix. The barplot on the left of the matrix shows the number of mutations in each gene. The percentages represent the fraction of tumors with at least one mutation in the specified gene. The barplot to the right of the matrix displays the q-values for the most significantly mutated genes. The purple boxplots below the matrix (only displayed if required columns are present in the provided MAF) represent the distributions of allelic fractions observed in each sample. The plot at the bottom represents the base substitution distribution of individual samples, using the same categories that were used to calculate significance.

Significantly Mutated Genes

Column Descriptions:

  • nnon = number of (nonsilent) mutations in this gene across the individual set

  • npat = number of patients (individuals) with at least one nonsilent mutation

  • nsite = number of unique sites having a non-silent mutation

  • nsil = number of silent mutations in this gene across the individual set

  • p = p-value (overall)

  • q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)

Table 1.  Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 25. Number of genes displayed: 35. Click on a gene name to display its stick figure depicting the distribution of mutations and mutation types across the chosen gene (this feature may not be available for all significant genes).

rank gene longname codelen nnei nncd nsil nmis nstp nspl nind nnon npat nsite pCV pCL pFN p q
1 FLT3 fms-related tyrosine kinase 3 3076 22 0 0 15 0 0 38 53 53 30 1e-16 1e-05 1e-05 1e-16 1.8e-13
2 NPM1 nucleophosmin (nucleolar phosphoprotein B23, numatrin) 936 1000 0 0 1 0 0 52 53 52 8 1.1e-15 1e-05 1e-05 1e-16 1.8e-13
3 DNMT3A DNA (cytosine-5-)-methyltransferase 3 alpha 2952 49 0 0 41 6 3 5 55 49 29 2.5e-15 1e-05 1e-05 1e-16 1.8e-13
4 IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial 1401 127 0 0 20 0 0 0 20 20 2 1e-16 1e-05 0.4 1e-16 1.8e-13
5 IDH1 isocitrate dehydrogenase 1 (NADP+), soluble 1277 543 0 0 18 0 0 0 18 18 2 1e-16 1e-05 1 1e-16 1.8e-13
6 RUNX1 runt-related transcription factor 1 (acute myeloid leukemia 1; aml1 oncogene) 1520 518 0 0 9 5 1 6 21 18 17 1e-16 0.12 0.0072 1e-16 1.8e-13
7 TET2 tet oncogene family member 2 6134 2 0 0 4 8 0 16 28 17 27 1e-16 0.71 1e-05 1e-16 1.8e-13
8 NRAS neuroblastoma RAS viral (v-ras) oncogene homolog 941 58 0 0 15 0 0 0 15 15 6 1e-16 1e-05 0.1 1e-16 1.8e-13
9 WT1 Wilms tumor 1 1590 100 0 0 2 0 2 9 13 12 11 1e-16 0.0025 1 1e-16 1.8e-13
10 U2AF1 U2 small nuclear RNA auxiliary factor 1 824 240 0 0 8 0 0 0 8 8 2 3.4e-16 1e-05 1e-05 1e-16 1.8e-13
11 TP53 tumor protein p53 1889 126 0 1 10 1 3 4 18 15 18 1e-16 1 0.066 6.7e-16 1.1e-12
12 CEBPA CCAAT/enhancer binding protein (C/EBP), alpha 1077 7 0 0 2 1 0 16 19 13 16 1e-16 0.28 0.79 1.6e-15 2.4e-12
13 PHF6 PHD finger protein 6 1241 591 0 0 2 1 1 2 6 6 6 6.9e-16 1 0.19 6.3e-15 8.9e-12
14 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 709 180 0 0 8 0 0 0 8 8 6 2.3e-13 0.012 0.65 9.9e-14 1.3e-10
15 SMC3 structural maintenance of chromosomes 3 3766 186 0 0 5 1 1 0 7 7 7 6.4e-14 1 0.18 2e-12 2.5e-09
16 KIT v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog 3013 32 0 0 7 0 0 3 10 8 6 9.8e-07 1e-05 0.23 2.6e-10 3e-07
17 RAD21 RAD21 homolog (S. pombe) 1948 61 0 0 0 2 0 3 5 5 5 5.2e-10 1 0.58 1.2e-08 0.000013
18 EZH2 enhancer of zeste homolog 2 (Drosophila) 2332 100 0 0 1 0 1 2 4 3 4 3.4e-07 0.0093 0.56 6.5e-08 0.000066
19 STAG2 stromal antigen 2 3939 7 0 0 0 3 3 0 6 6 6 7.1e-09 1 0.92 1.4e-07 0.00014
20 PTPN11 protein tyrosine phosphatase, non-receptor type 11 (Noonan syndrome 1) 1842 24 0 0 9 0 0 0 9 9 9 3e-08 1 0.28 5.6e-07 0.00051
21 ASXL1 additional sex combs like 1 (Drosophila) 4678 29 0 0 0 2 1 2 5 5 5 7.8e-08 1 0.87 1.4e-06 0.0012
22 HNRNPK heterogeneous nuclear ribonucleoprotein K 1488 179 0 0 0 0 0 3 3 2 3 0.000039 0.0054 0.48 3.8e-06 0.0031
23 ABTB1 ankyrin repeat and BTB (POZ) domain containing 1 1554 196 0 0 0 0 0 2 2 2 1 0.00016 0.01 0.93 0.000023 0.018
24 GIGYF2 GRB10 interacting GYF protein 2 4823 17 0 0 0 0 0 2 2 2 2 0.00047 0.01 0.93 0.000062 0.048
25 SUZ12 suppressor of zeste 12 homolog (Drosophila) 2280 34 0 0 2 0 0 1 3 3 3 6e-06 1 0.87 0.000078 0.057
26 PHACTR1 phosphatase and actin regulator 1 1795 63 0 0 1 0 0 2 3 3 2 0.0014 0.0093 0.65 0.00018 0.12
27 SMC1A structural maintenance of chromosomes 1A 3800 46 0 0 5 1 0 0 6 6 6 0.00012 1 0.1 0.00027 0.19
28 KDM6A lysine (K)-specific demethylase 6A 4318 35 0 0 2 0 1 0 3 3 3 0.000037 1 0.31 0.00042 0.27
29 C17orf97 chromosome 17 open reading frame 97 919 378 0 0 2 0 0 0 2 2 2 0.00047 NaN NaN 0.00047 0.3
30 PKD1L2 polycystic kidney disease 1-like 2 7615 310 0 2 2 0 0 0 2 2 2 0.00071 1 0.032 0.00048 0.3
31 THRAP3 thyroid hormone receptor associated protein 3 2908 104 0 0 1 1 0 0 2 2 2 0.00026 1 0.16 0.00067 0.39
32 CBL Cas-Br-M (murine) ecotropic retroviral transforming sequence 2781 104 0 1 1 0 1 0 2 2 2 0.000066 1 0.47 0.00071 0.39
33 STRN striatin, calmodulin binding protein 2413 83 0 0 1 0 0 1 2 2 2 0.00016 1 0.34 0.00071 0.39
34 RBBP4 retinoblastoma binding protein 4 1677 260 0 0 2 0 0 0 2 2 1 0.0095 0.01 0.66 0.00097 0.52
35 ZBTB33 zinc finger and BTB domain containing 33 2023 361 0 0 2 0 0 0 2 2 2 0.0001 1 0.12 0.001 0.54
Methods & Data
Methods

In brief, we tabulate the number of mutations and the number of covered bases for each gene. The counts are broken down by mutation context category: four context categories that are discovered by MutSig, and one for indel and 'null' mutations, which include indels, nonsense mutations, splice-site mutations, and non-stop (read-through) mutations. For each gene, we calculate the probability of seeing the observed constellation of mutations, i.e. the product P1 x P2 x ... x Pm, or a more extreme one, given the background mutation rates calculated across the dataset. [1]

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] TCGA, Integrated genomic analyses of ovarian carcinoma, Nature 474:609 - 615 (2011)
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